Uneven distribution of data becomes problematic with storage capacity increases, frequent changes of data, and a limited routing table. This problem has been addressed in part by recommending subtree migrations between metadata servers or analysing latency of queries. Although methods for load distributing exist, existing techniques suffer from one or more disadvantages.
In particular, metadata stores provide information about a collection of data. Typically, metadata servers contain data organized in mapped files and directories that enable the discovering of relevant information. This data dynamically changes in a metadata store as contents and references are added, removed, or restructured. These changes disturb the efficiency and performance of the metadata store, possibly resulting in overloading certain memory clusters. Failure to implement a load balancing strategy to downsize the certain memory clusters in the metadata store leads to a potential performance bottleneck due to uneven distribution of data.